1 Introduction

The objective of this notebook is to cluster cells at a low resolution that allows us to “fetch” the clusters that are potential doublets, so that we can easily exclude them.

2 Pre-processing

2.1 Load packages

library(Seurat)
library(tidyverse)

2.2 Parameters

# Paths
path_to_obj <- str_c(
  here::here("scRNA-seq/results/R_objects/level_2/"),
  cell_type,
  "/",
  cell_type,
  "_integrated_level_2.rds",
  sep = ""
)


# Functions
source(here::here("scRNA-seq/bin/utils.R"))


# Colors
color_palette <- c("black", "gray", "red", "yellow", "violet", "green4",
                   "blue", "chocolate1", "coral2", "blueviolet",
                   "brown1", "darkmagenta", "deepskyblue1", "dimgray",
                   "deeppink1", "green", "lightgray", "hotpink1",
                   "indianred4", "khaki", "mediumorchid2")

2.3 Load data

# Seurat object
seurat <- readRDS(path_to_obj)
seurat
## An object of class Seurat 
## 37378 features across 126532 samples within 1 assay 
## Active assay: RNA (37378 features, 0 variable features)
##  3 dimensional reductions calculated: pca, umap, harmony

3 Cluster

resolutions <- c(0.025, 0.05, 0.1, 0.2, 0.3, 0.4)
seurat <- FindClusters(seurat, resolution = resolutions)
## Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
## 
## Number of nodes: 126532
## Number of edges: 2743967
## 
## Running Louvain algorithm...
## Maximum modularity in 10 random starts: 0.9750
## Number of communities: 29
## Elapsed time: 48 seconds
## Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
## 
## Number of nodes: 126532
## Number of edges: 2743967
## 
## Running Louvain algorithm...
## Maximum modularity in 10 random starts: 0.9560
## Number of communities: 30
## Elapsed time: 48 seconds
## Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
## 
## Number of nodes: 126532
## Number of edges: 2743967
## 
## Running Louvain algorithm...
## Maximum modularity in 10 random starts: 0.9362
## Number of communities: 32
## Elapsed time: 48 seconds
## Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
## 
## Number of nodes: 126532
## Number of edges: 2743967
## 
## Running Louvain algorithm...
## Maximum modularity in 10 random starts: 0.9154
## Number of communities: 36
## Elapsed time: 52 seconds
## Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
## 
## Number of nodes: 126532
## Number of edges: 2743967
## 
## Running Louvain algorithm...
## Maximum modularity in 10 random starts: 0.8972
## Number of communities: 37
## Elapsed time: 53 seconds
## Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
## 
## Number of nodes: 126532
## Number of edges: 2743967
## 
## Running Louvain algorithm...
## Maximum modularity in 10 random starts: 0.8821
## Number of communities: 40
## Elapsed time: 49 seconds
vars <- str_c("RNA_snn_res.", resolutions)
umap_clusters <- purrr::map(vars, function(x) {
  p <- DimPlot(seurat, group.by = x, cols = color_palette)
  p
})
umap_clusters
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4 Session Information

sessionInfo()
## R version 3.6.0 (2019-04-26)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Red Hat Enterprise Linux Server release 6.7 (Santiago)
## 
## Matrix products: default
## BLAS:   /apps/R/3.6.0/lib64/R/lib/libRblas.so
## LAPACK: /home/devel/rmassoni/anaconda3/lib/libmkl_rt.so
## 
## locale:
##  [1] LC_CTYPE=C                 LC_NUMERIC=C               LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8     LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8    LC_PAPER=en_US.UTF-8       LC_NAME=C                  LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] forcats_0.5.0    stringr_1.4.0    dplyr_1.0.4      purrr_0.3.4      readr_1.3.1      tidyr_1.1.0      tibble_3.0.1     ggplot2_3.3.0    tidyverse_1.3.0  Seurat_3.2.0     BiocStyle_2.14.4
## 
## loaded via a namespace (and not attached):
##   [1] Rtsne_0.15            colorspace_1.4-1      deldir_0.1-25         ellipsis_0.3.1        ggridges_0.5.2        rprojroot_1.3-2       fs_1.4.1              rstudioapi_0.11       spatstat.data_1.4-3   farver_2.0.3          leiden_0.3.3          listenv_0.8.0         ggrepel_0.8.2         fansi_0.4.1           lubridate_1.7.8       xml2_1.3.2            codetools_0.2-16      splines_3.6.0         knitr_1.28            polyclip_1.10-0       jsonlite_1.7.2        broom_0.5.6           ica_1.0-2             cluster_2.1.0         dbplyr_1.4.4          png_0.1-7             uwot_0.1.8            shiny_1.4.0.2         sctransform_0.2.1     BiocManager_1.30.10   compiler_3.6.0        httr_1.4.2            backports_1.1.7       assertthat_0.2.1      Matrix_1.2-18         fastmap_1.0.1         lazyeval_0.2.2        cli_2.0.2             later_1.0.0           htmltools_0.5.1.1     tools_3.6.0           rsvd_1.0.3            igraph_1.2.5          gtable_0.3.0          glue_1.4.1            RANN_2.6.1            reshape2_1.4.4        rappdirs_0.3.1        Rcpp_1.0.6            spatstat_1.64-1       cellranger_1.1.0      vctrs_0.3.6           ape_5.3               nlme_3.1-148         
##  [55] lmtest_0.9-37         xfun_0.14             globals_0.12.5        rvest_0.3.5           mime_0.9              miniUI_0.1.1.1        lifecycle_0.2.0       irlba_2.3.3           goftest_1.2-2         future_1.17.0         MASS_7.3-51.6         zoo_1.8-8             scales_1.1.1          hms_0.5.3             promises_1.1.0        spatstat.utils_1.17-0 parallel_3.6.0        RColorBrewer_1.1-2    yaml_2.2.1            reticulate_1.16       pbapply_1.4-2         gridExtra_2.3         rpart_4.1-15          stringi_1.4.6         rlang_0.4.10          pkgconfig_2.0.3       evaluate_0.14         lattice_0.20-41       ROCR_1.0-11           tensor_1.5            labeling_0.3          patchwork_1.0.0       htmlwidgets_1.5.1     cowplot_1.0.0         tidyselect_1.1.0      here_0.1              RcppAnnoy_0.0.16      plyr_1.8.6            magrittr_1.5          bookdown_0.19         R6_2.4.1              generics_0.0.2        DBI_1.1.0             withr_2.4.1           pillar_1.4.4          haven_2.3.1           mgcv_1.8-31           fitdistrplus_1.1-1    survival_3.1-12       abind_1.4-5           future.apply_1.5.0    modelr_0.1.8          crayon_1.3.4          KernSmooth_2.23-17   
## [109] plotly_4.9.2.1        rmarkdown_2.2         readxl_1.3.1          grid_3.6.0            data.table_1.12.8     blob_1.2.1            reprex_0.3.0          digest_0.6.20         xtable_1.8-4          httpuv_1.5.3.1        munsell_0.5.0         viridisLite_0.3.0